The field of the invention relates generally to computerized generation of links between merchants and cardholders, more specifically, to systems and methods for generating connections between merchants and cardholders using a graph database based on transaction data.
As a matter of background, transaction data (e.g., payment data) may include data processed by a payment card processor over a payment network. Typically, such transaction data arrive at the payment processor and are stored in a data warehouse as individual records in a disconnected form. Individual records may be stored in a database, with tabulated records connected using unique identifiers. Thus, most models used for modeling such transaction data are based on properties of individual entities (i.e., cards, merchants, etc.).
However, a tremendous amount of information and insight is lost by retaining transaction data in tabular form, such as in a relational database table. It is cumbersome to detect whether individual records are connected across tables in any useful ways. More specifically, it is difficult to determine whether, for example, merchant records or payment cards stored in disconnected tables exhibit any common characteristics or linkages. At least some known methods of interconnecting tabulated data involve joining multiple tables. However, with large datasets containing millions or billions of records (e.g., those for merchants and payment cards), joining multiple tables to extract any useful information becomes tedious, if not impossible.